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Michael Teutsch, Angel Sappa & Riad Hammoud |
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Computer Vision in the Infrared Spectrum: Challenges and ApproachesComputer Vision in the Infrared Spectrum: Challenges and Approaches |
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2021 |
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Synthesis Lectures on Computer Vision |
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Vol. 10 No. 2 |
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pp. 138 |
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cidis @ cidis @ |
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166 |
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Patricia L. Suárez, Angel D. Sappa and Boris X. Vintimilla |
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Deep learning-based vegetation index estimation |
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2021 |
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Generative Adversarial Networks for Image-to-Image Translation Book. |
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Chapter 9 |
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Issue 2 |
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205-232 |
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cidis @ cidis @ |
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137 |
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Patricia L. Suárez, Angel D. Sappa, Boris X. Vintimilla |
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Title |
Cycle generative adversarial network: towards a low-cost vegetation index estimation |
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2021 |
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IEEE International Conference on Image Processing (ICIP 2021) |
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2021-September |
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2783-2787 |
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CyclicGAN, NDVI, near infrared spectra, instance normalization. |
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This paper presents a novel unsupervised approach to estimate the Normalized Difference Vegetation Index (NDVI).The NDVI is obtained as the ratio between information from the visible and near infrared spectral bands; in the current work, the NDVI is estimated just from an image of the visible spectrum through a Cyclic Generative Adversarial Network (CyclicGAN). This unsupervised architecture learns to estimate the NDVI index by means of an image translation between the red channel of a given RGB image and the NDVI unpaired index’s image. The translation is obtained by means of a ResNET architecture and a multiple loss function. Experimental results obtained with this unsupervised scheme show the validity of the implemented model. Additionally, comparisons with the state of the art approaches are provided showing improvements with the proposed approach. |
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cidis @ cidis @ |
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164 |
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Patricia L. Suárez, Dario Carpio, and Angel Sappa |
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Non-Homogeneous Haze Removal through a Multiple Attention Module Architecture. |
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2021 |
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16 International Symposium on Visual Computing. Octubre 4-6, 2021. Lecture Notes in Computer Science |
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13018 |
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178-190 |
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cidis @ cidis @ |
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162 |
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